[seek-kr-sms] OBOE discussion: current version

[Deana Pennington]

I hate to complicate this further, but I think we have to deal with 
perdurants.  Use case scenario:  we want to combine biomass data from 
two different field sites.  Site 1 has measured biomass 2x per year 
(spring and fall) for 5 years, and has stored all of this in a single 
dataset.  Site 2 has measured biomass 1x per year (fall only) for 10 
years that partially overlap the other study, and has each year in a 
separate dataset.  We have the data from site 1, we want to query to 
discover any overlapping data, and then construct a new integrated 
dataset (fall data for the overlapping years).  To capture these 
relationships we have to recognize separate events within a given 
dataset, which gets back to Sergey's comment about relationships between 
rows.  We also would have to annotate temporal relationships BETWEEN 
datasets (ick - I hate to even bring this up!), unless we think the 
system is going to be smart enough to figure out those relationships 
from the metadata (I don't think so).  Maybe we need to keep OBOE as an 
ontology of endurant's, but have a perdurant ontology that can be used 
to describe event relationships?   At that point, I think you are trying 
to describe how a particular set of concrete observations fits into an 
abstract observing framework that is not instantiated anywhere except in 
the mind of the observer, but needs to be constructed by the reasoner.  
Does this make sense to anyone???  There is an analogous problem with 
space.  I'm thinking about the spatial problem, especially with Bob 
Morris raising the imagery issues.  Might need to get a subgroup 
together to start work on that.  We need to consider how (if?) other 
data representations such as imagery work under the OBOE framework.

Maybe what we need is a higher level framework that describes endurants 
and perdurants, linking space, time, and observation?   Are there other 
high level concepts that belong at that level?

Deana


Ferdinando Villa wrote:
> To express the points below (Measurement as event) more fully: the 
> whole contextualization business is the part of the Observation that 
> relates to the event of observing. In order to describe the 
> Observable, we must observe it, and in order to observe it, we must 
> define a space/time/method/treatment/etc context - be there, at that 
> time, use that method etc. The Observation as a "result of the event 
> of observing" needs contextual observations in order to 
> characterize the event. So if we want to see observation as an event, 
> it is a whole new ontology we're talking about - one of perdurants. 
> Our datasets are endurants and require that OBOE is an ontology of 
> endurants, which crystallizes the RESULT of the observation process. 
> Our hasContext relationship translates the 
> perdurant space/time/method/etc context of the event Observation into 
> endurant Observations that can be recorded in a dataset.
>  
> I would also postulate that an annotation must contain one and only 
> one Observation that is not the target of a hasContext relationship. 
> If more than one appear during an annotation, we have more than one 
> separate datasets in the same physical storage.
>  
>  I totally agree and there has been some discussion about this.  I 
> really like your use of the word "event", I think this makes what we 
> are actually doing much clearer.  For example, we Observe a tree, each 
> Measurement is an event relating to that Observation, and a 
> Measurement is of some characteristic.  I second the move changing the 
> property between Observation and Meaurement to something like 
> "hasMeasurementEvent".  
>
>          
>          
>         Our definition, if I remember correctly, was :Observation is a
>         statement that an Observable has been observed. I think more
>         than this is going to color OBOE with restrictions it does not
>         need to have. By the way, we model the result of the
>         observation, not the process of the observation, and the
>         result is not an event. To annotate a dataset we don't need to
>         know anything about the measurement except its results.  
>          
>
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-- 
********

Deana D. Pennington, PhD
Long-term Ecological Research Network Office

UNM Biology Department
MSC03  2020
1 University of New Mexico
Albuquerque, NM  87131-0001

505-277-2595 (office)
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